Decentralised Learning in Systems With Many, Many Strategic Agents. - David Mguni; Joel Jennings; Enrique Munoz de Cote (AAAI, 2018)

Coordinating the Crowd: Inducing Desirable Equilibria in Non-Cooperative Systems. - David Mguni; Joel Jennings; Emilio Sison; Sergio Valcarcel Macua; Sofia Ceppi; Enrique Munoz de Cote (AAMAS, 2019)

Cutting Your Losses: Learning Fault-Tolerant Control and Optimal Stopping under Adverse Risk. - David Mguni (CoRR, 2019)

Multi-Agent Determinantal Q-Learning. - Yaodong Yang 001; Ying Wen 001; Jun Wang 012; Liheng Chen; Kun Shao; David Mguni; Weinan Zhang 001 (ICML, 2020)

Learning in Nonzero-Sum Stochastic Games with Potentials. - David Henry Mguni; Yutong Wu 005; Yali Du 001; Yaodong Yang 001; Ziyi Wang 004; Minne Li; Ying Wen 001; Joel Jennings; Jun Wang 012 (ICML, 2021)

Modelling Behavioural Diversity for Learning in Open-Ended Games. - Nicolas Perez Nieves; Yaodong Yang 001; Oliver Slumbers; David Henry Mguni; Ying Wen 001; Jun Wang 012 (ICML, 2021)

Settling the Variance of Multi-Agent Policy Gradients. - Jakub Grudzien Kuba; Muning Wen; Linghui Meng 001; Shangding Gu; Haifeng Zhang 002; David Mguni; Jun Wang 012; Yaodong Yang 001 (NeurIPS, 2021)

Online Double Oracle. - Le Cong Dinh; Yaodong Yang 001; Zheng Tian 002; Nicolas Perez Nieves; Oliver Slumbers; David Henry Mguni; Haitham Bou-Ammar; Jun Wang 012 (CoRR, 2021)

Modelling Behavioural Diversity for Learning in Open-Ended Games. - Nicolas Perez Nieves; Yaodong Yang 001; Oliver Slumbers; David Henry Mguni; Jun Wang 012 (CoRR, 2021)

Learning to Shape Rewards using a Game of Switching Controls. - David Mguni; Jianhong Wang; Taher Jafferjee; Nicolas Perez Nieves; Wenbin Song; Yaodong Yang 001; Feifei Tong; Hui Chen; Jiangcheng Zhu; Yali Du 001; Jun Wang 012 (CoRR, 2021)

DESTA: A Framework for Safe Reinforcement Learning with Markov Games of Intervention. - David Mguni; Joel Jennings; Taher Jafferjee; Aivar Sootla; Yaodong Yang 001; Changmin Yu; Usman Islam; Ziyan Wang; Jun Wang 012 (CoRR, 2021)

On the Complexity of Computing Markov Perfect Equilibrium in General-Sum Stochastic Games. - Xiaotie Deng; Yuhao Li 002; David Mguni; Jun Wang 012; Yaodong Yang 001 (Electron. Colloquium Comput. Complex., 2021)

Socially-Attentive Policy Optimization in Multi-Agent Self-Driving System. - Zipeng Dai; Tianze Zhou; Kun Shao; David Henry Mguni; Bin Wang 034; Jianye Hao (CoRL, 2022)

LIGS: Learnable Intrinsic-Reward Generation Selection for Multi-Agent Learning. - David Henry Mguni; Taher Jafferjee; Jianhong Wang; Nicolas Perez Nieves; Oliver Slumbers; Feifei Tong; Yang Li 116; Jiangcheng Zhu; Yaodong Yang 001; Jun Wang 012 (ICLR, 2022)

Saute RL: Almost Surely Safe Reinforcement Learning Using State Augmentation. - Aivar Sootla; Alexander I. Cowen-Rivers; Taher Jafferjee; Ziyan Wang; David Henry Mguni; Jun Wang 012; Haitham Ammar (ICML, 2022)

On the Convergence of Fictitious Play: A Decomposition Approach. - Yurong Chen 002; Xiaotie Deng; Chenchen Li; David Mguni; Jun Wang 012; Xiang Yan; Yaodong Yang 001 (IJCAI, 2022)

SEREN: Knowing When to Explore and When to Exploit. - Changmin Yu; David Mguni; Dong Li 016; Aivar Sootla; Jun Wang 012; Neil Burgess (CoRR, 2022)

Learning Risk-Averse Equilibria in Multi-Agent Systems. - Oliver Slumbers; David Henry Mguni; Stephen McAleer; Jun Wang 012; Yaodong Yang 001 (CoRR, 2022)

Semi-Centralised Multi-Agent Reinforcement Learning with Policy-Embedded Training. - Taher Jafferjee; Juliusz Krysztof Ziomek; Tianpei Yang; Zipeng Dai; Jianhong Wang; Matthew E. Taylor; Kun Shao; Jun Wang 012; David Mguni (CoRR, 2022)

Online Double Oracle. - Le Cong Dinh; Stephen Marcus McAleer; Zheng Tian 002; Nicolas Perez Nieves; Oliver Slumbers; David Henry Mguni; Jun Wang 012; Haitham Bou-Ammar; Yaodong Yang 001 (Trans. Mach. Learn. Res., 2022)

Learning to Shape Rewards Using a Game of Two Partners. - David Mguni; Taher Jafferjee; Jianhong Wang; Nicolas Perez Nieves; Wenbin Song; Feifei Tong; Matthew E. Taylor; Tianpei Yang; Zipeng Dai; Hui Chen; Jiangcheng Zhu; Kun Shao; et al. (AAAI, 2023)

Timing is Everything: Learning to Act Selectively with Costly Actions and Budgetary Constraints. - David Henry Mguni; Aivar Sootla; Juliusz Ziomek; Oliver Slumbers; Zipeng Dai; Kun Shao; Jun Wang 012 (ICLR, 2023)

MANSA: Learning Fast and Slow in Multi-Agent Systems. - David Henry Mguni; Haojun Chen; Taher Jafferjee; Jianhong Wang; Longfei Yue; Xidong Feng; Stephen Marcus McAleer; Feifei Tong; Jun Wang 012; Yaodong Yang 001 (ICML, 2023)

A Game-Theoretic Framework for Managing Risk in Multi-Agent Systems. - Oliver Slumbers; David Henry Mguni; Stefano B. Blumberg; Stephen Marcus McAleer; Yaodong Yang 001; Jun Wang 012 (ICML, 2023)

ChessGPT: Bridging Policy Learning and Language Modeling. - Xidong Feng; Yicheng Luo; Ziyan Wang; Hongrui Tang; Mengyue Yang; Kun Shao; David Mguni; Yali Du 001; Jun Wang 012 (NeurIPS, 2023)

MANSA: Learning Fast and Slow in Multi-Agent Systems. - David Mguni; Taher Jafferjee; Haojun Chen; Jianhong Wang; Long Fei; Xidong Feng; Stephen McAleer; Feifei Tong; Jun Wang 012; Yaodong Yang 001 (CoRR, 2023)

Ask more, know better: Reinforce-Learned Prompt Questions for Decision Making with Large Language Models. - Xue Yan; Yan Song 003; Xinyu Cui; Filippos Christianos; Haifeng Zhang 002; David Henry Mguni; Jun Wang 012 (CoRR, 2023)

Online Markov decision processes with non-oblivious strategic adversary. - Le Cong Dinh; David Henry Mguni; Long Tran-Thanh; Jun Wang 012; Yaodong Yang 001 (Auton. Agents Multi Agent Syst., 2023)

A Summary of Online Markov Decision Processes with Non-oblivious Strategic Adversary. - Le Cong Dinh; David Henry Mguni; Long Tran-Thanh; Jun Wang 012; Yaodong Yang 001 (AAMAS, 2024)

All Language Models Large and Small. - Zhixun Chen; Yali Du 001; David Mguni (CoRR, 2024)

Stochastic Games with Minimally Bounded Action Costs. - David Mguni (CoRR, 2024)

A survey on algorithms for Nash equilibria in finite normal-form games. - Hanyu Li; Wenhan Huang; Zhijian Duan 001; David Henry Mguni; Kun Shao; Jun Wang 012; Xiaotie Deng (Comput. Sci. Rev., 2024)

Ensemble Value Functions for Efficient Exploration in Multi-Agent Reinforcement Learning. - Lukas Schäfer 001; Oliver Slumbers; Stephen McAleer; Yali Du 001; Stefano V. Albrecht; David Mguni (AAMAS, 2025)

Taming Multi-Agent Reinforcement Learning with Estimator Variance Reduction. - Taher Jafferjee; Juliusz Ziomek; Tianpei Yang; Zipeng Dai; Jianhong Wang; Matthew E. Taylor; Kun Shao; Jun Wang 012; David Mguni (AAMAS, 2025)

Fault Tolerant Multi-Agent Learning with Adversarial Budget Constraints. - David Mguni; Yaqi Sun; Haojun Chen; Amir Darabi; Larry Olanrewaju Orimoloye; Yaodong Yang 001 (CoRR, 2025)